FLIR's FC-series installation manual, available on-line at the following link: Http://flir.com/uploadedfiles/CVS_Americas/Security_-_NEW/Products/FC-Series/FLIR-FC-Series-S-Installation-Manual.pdf instructs, on page 3-6, that:
“To set the Human Size properties, have a person walk around at the bottom of the area and adjust the Human Size Near Width and Near Height parameters so the blue box (near human) is the same size as the yellow detection box. Click Save. Then, have the person walk around at the top of the area and adjust the Human Size Far Width and Far Height parameters so the purple box (far human) is the same size as the yellow detection box around them. Click Save. The yellow detection box will change to orange when it fits between the minimum (far human) and maximum (near human) bounding boxes. Set the Human Size Tolerance to allow for expected variations in the detected person size. A tolerance of 10% will cause the Near bounding box to increase by 10% and the Far bounding box to decrease by 10%. The tolerance is set independently for Human Size and Vehicle Size. Repeat this same exercise using an appropriate vehicle to determine the Vehicle Size parameters. Finally, set the Vehicle Size Tolerance to allow for expected variations in the detected vehicle size. A tolerance of 10% will cause the Near bounding box to increase by 10% and the Far bounding box to decrease by 10%. The tolerance is set independently for Human Size and Vehicle Size.’
U.S. Pat. No. 9,282,296 to Gao describes a method for determining relationships between cameras: “In act 62 of FIG. 2, any relationship of a camera with one or more other cameras is received. The processor receives the interrelationship information in response to input from the user. The user indicates whether and/or how the cameras are related. The relationship may be for field of view overlap, for viewing a same location, or for being connected by traffic flow. For example, an exit/entry point (e.g., transition point) in one field of view may lead to a hallway with an exit/entry point at another end in a field of view of the other camera. The cameras are related such that traffic from one progresses to the other even though the fields of view do not overlap . . . .
Hotspots define valid places (e.g., hallways or doors) that a person could enter or leave the view . . . .
One or more hotspots are defined. The hotspots are locations associated with the video analytics. In one example, the hotspots are entry and exit locations of the field of view of the camera. In other examples, the hotspot is additionally or alternatively a location where a person, license plate, or other distinguishing feature is more likely viewable by the camera. Other hotspots depending on the type of analytics performed may be used. The hotspots are entered on the image, but may be alternatively designated on the map. The user defines the hotspot using the paint tool . . . . One or more hotspots are automatically generated . . . . Tracking moving objects may be used to automatically detect hotspots. The locations, such as foot locations, at which people appear or disappear in a field of view or scene from a camera are detected. The density of these occurrences may indicate a hotspot.”
The disclosures of all publications and patent documents mentioned in the specification, and of the publications and patent documents cited therein directly or indirectly, are hereby incorporated by reference. Materiality of such publications and patent documents to patentability is not conceded.